(T, thresh) = cv2.threshold(dilated, 3, 255, cv2.THRESH_BINARY) Anything pixel that has #value higher than 3 we are converting to white #(remember 0 is black and 255 is exact white) #the image is called binarised as any value lower than 3 will be 0 and # all of the values equal to and higher than 3 will be 255 In this section of the code, we first convert the images into grayscale that help in making and applying different types of operations on the images really easy and then we apply morphological operation (Morphological Operations is a broad set of image processing operations that can process digital images based on their shapes and sizes.) on the images to merge the pixel together, as we are not really interested in the exact difference but er are really interested in the region of difference on images. #increasing the size of differences after that we can capture them all for i in range(0, 3):ĭilated = cv2.dilate(py(), None, iterations= i+ 1) Gray = cv2.cvtColor(diff, cv2.COLOR_BGR2GRAY) #converting the difference into grayscale images The difference is returned in the third argument. With the help of this function, we will be able to calculate per-element exact difference between two arrays. Now we have to use the function absdiff that helps to find the absolute difference between the pixels of the two image arrays. #create a copy of original image so that we can store the #difference of 2 images in the same on Now we can also work with the original images themselves, although sometimes images are really large in size for that reason it may take significantly more time to process the images. Once the images are fully loaded, we need to resize the images to a more manageable size(high = 960pixels in this case). Original = imutils.resize(original, height = 600)Īfter that we need to read the images from the system memory, we need to make sure that both the images are placed in the same folder as the code that we are writing, else you need to provide the location path of the images. A bigger size image may take a significant time #resize the images to make them small in size. We can easily install imutils using the “ pip install imutils” command. Then we need to import the required libraries including openCV as well as utils. Now open your favourite code editor and paste the below code: import cv2 Now open the terminal and install the required packages using the below commands: Knowledge of Python Step – 1: Installing the Package. The operation cv2.subtract(image1,image2) instead of arithmetic operation and simply subtract each pixel from the first image to the value of the corresponding pixel in the second image. If both of the images have the same sizes and channels, we can proceed by subtracting them. if both of the images have the same size and channels, we have to continue forward with the operation, if both of the images don’t have the same size and channels then they are not equal. Let’s start by checking if they have the same size and channels.
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